Simran Lalwani.
ML engineer · 3D Perception · San Francisco
I like to build things. AI is just my sharpest tool.
Same aerial frame, four Cosmos-Transfer2.5 outputs. The pipeline that generated and validated 47k+ annotations on A100-80GB, feeding controlled domain-transfer ablations for downstream detectors.
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I have an MS in Data Science from RIT and have been building perception systems for autonomous navigation, edge AI, and public safety.
My research spans neuroevolution for drone flight safety (RNN architecture search on real NGAFID telemetry with Prof. Travis Desell) and domain generalization for time-series classification across unseen distributions using ECG data, with Dr. Linwei Wang.
At OWL Autonomous Imaging I built MGNet, a thermal+RGB dual-encoder fusion model for panoptic segmentation and monocular depth estimation, lifting navigation mIoU by 20%. I also shipped real-time super-resolution and denoising for 16-bit sensor streams and built an annotation tool that cut labeling time by 40% across 50K+ frames. At Alta Potentia I deployed YOLOv8 on NVIDIA Jetson at sub-100ms latency with TensorRT, processing 500K+ frames for retail loss prevention.
Most recently: Cosmos-Overwatch , a synthetic data platform using NVIDIA Cosmos-Transfer2.5 to generate domain-shifted aerial footage (rain, fog, thermal, night-fire) with dual edge+depth control, validated across 47K+ MOT-compatible annotations.
I'm looking for perception engineering roles in autonomous vehicles, robotics, or drone systems: 3D perception, multimodal sensor fusion (camera/LiDAR/radar), models running on millions of devices or thousands of missions under real-world constraints.